scholarly journals A Robust Region Control Approach for Simultaneous Trajectory Tracking and Physical Human-Robot Interaction

Author(s):  
Xiangyun Li ◽  
QI LU ◽  
Jiali Chen ◽  
Kang Li

In this work, the uncertainty and disturbance estimator (UDE)-based robust region tracking controller for a robot manipulator is developed to achieve the moving target region trajectory tracking and the compliant human-robot interaction simultaneously. Utilizing the back-stepping control approach, the UDE is seamlessly fused into the region tracking control framework to estimate and compensate the model uncertainty and external disturbance, such as unknown payload, unmodeled joint coupling effect and friction. The regional feedback error is derived from the potential function to drive the robot manipulator end-effector converging into the target region, where the robot manipulator can be passively manipulated based on the needs of human to achieve the compliant physical human-robot interaction. Extensive experimental studies are carried out with a universal robots 10 manipulator to validate the effectiveness of the proposed method for moving region trajectory tracking, handling unknown payload and compliant physical human-robot interaction. The superior robustness of the proposed approach is demonstrated by comparison with the existing controller under the adverse effect of unknown payload. The humanrobot interaction is achieved in a shared autonomy manner with the cooperation of the manipulator and the human subject to accomplish the temperature measurement task, where the variation in human-subject height and the complexity of aiming the thermometer are successfully accommodated.

2021 ◽  
Author(s):  
xiangyun Li ◽  
QI LU ◽  
Zhaoyang Chen ◽  
Qinlin Yang ◽  
Kang Li

n this work, the uncertainty and disturbance estimator (UDE)-based robust region reaching controller for a robot manipulator is developed to achieve the moving target region trajectory tracking and complaint human robot interaction inside the target region. The regional feedback error is derived from the potential function to drive the robot manipulator end effector converging into the target region. Under the back-stepping control framework, the UDE is fused into the region tracking control law to estimate and compensate the model uncertainty and external disturbance. Both simulation and experimental studies are carried out with a universal robots (UR) 10 manipulator to demonstrate the effectiveness of the proposed method for moving target trajectory tracking, model uncertainty and external disturbance rejection, and compliant human robot interaction within the target region.


2021 ◽  
Author(s):  
xiangyun Li ◽  
QI LU ◽  
Zhaoyang Chen ◽  
Qinlin Yang ◽  
Kang Li

n this work, the uncertainty and disturbance estimator (UDE)-based robust region reaching controller for a robot manipulator is developed to achieve the moving target region trajectory tracking and complaint human robot interaction inside the target region. The regional feedback error is derived from the potential function to drive the robot manipulator end effector converging into the target region. Under the back-stepping control framework, the UDE is fused into the region tracking control law to estimate and compensate the model uncertainty and external disturbance. Both simulation and experimental studies are carried out with a universal robots (UR) 10 manipulator to demonstrate the effectiveness of the proposed method for moving target trajectory tracking, model uncertainty and external disturbance rejection, and compliant human robot interaction within the target region.


2019 ◽  
Vol 10 (1) ◽  
pp. 256-266
Author(s):  
Fabio Vannucci ◽  
Alessandra Sciutti ◽  
Hagen Lehman ◽  
Giulio Sandini ◽  
Yukie Nagai ◽  
...  

AbstractIn social interactions, human movement is a rich source of information for all those who take part in the collaboration. In fact, a variety of intuitive messages are communicated through motion and continuously inform the partners about the future unfolding of the actions. A similar exchange of implicit information could support movement coordination in the context of Human-Robot Interaction. In this work, we investigate how implicit signaling in an interaction with a humanoid robot can lead to emergent coordination in the form of automatic speed adaptation. In particular, we assess whether different cultures – specifically Japanese and Italian – have a different impact on motor resonance and synchronization in HRI. Japanese people show a higher general acceptance toward robots when compared with Western cultures. Since acceptance, or better affiliation, is tightly connected to imitation and mimicry, we hypothesize a higher degree of speed imitation for Japanese participants when compared to Italians. In the experimental studies undertaken both in Japan and Italy, we observe that cultural differences do not impact on the natural predisposition of subjects to adapt to the robot.


Author(s):  
Akimul Prince ◽  
Biswanath Samanta

The paper presents a control approach based on vertebrate neuromodulation and its implementation on an autonomous robot platform. A simple neural network is used to model the neuromodulatory function for generating context based behavioral responses to sensory signals. The neural network incorporates three types of neurons — cholinergic and noradrenergic (ACh/NE) neurons for attention focusing and action selection, dopaminergic (DA) neurons for curiosity-seeking, and serotonergic (5-HT) neurons for risk aversion behavior. The implementation of the neuronal model on a relatively simple autonomous robot illustrates its interesting behavior adapting to changes in the environment. The integration of neuromodulation based robots in the study of human-robot interaction would be worth considering in future.


Author(s):  
Monisha Pathak* ◽  
◽  
Dr. Mrinal Buragohain ◽  

This paper briefly discusses about the Robust Controller based on Adaptive Sliding Mode Technique with RBF Neural Network (ASMCNN) for Robotic Manipulator tracking control in presence of uncertainities and disturbances. The aim is to design an effective trajectory tracking controller without any modelling information. The ASMCNN is designed to have robust trajectory tracking of Robot Manipulator, which combines Neural Network Estimation with Adaptive Sliding Mode Control. The RBF model is utilised to construct a Lyapunov function-based adaptive control approach. Simulation of the tracking control of a 2dof Robotic Manipulator in the presence of unpredictability and external disruption demonstrates the usefulness of the planned ASMCNN.


Author(s):  
Mustafa Can Bingol ◽  
Omur Aydogmus

Purpose Because of the increased use of robots in the industry, it has become inevitable for humans and robots to be able to work together. Therefore, human security has become the primary noncompromising factor of joint human and robot operations. For this reason, the purpose of this study was to develop a safe human-robot interaction software based on vision and touch. Design/methodology/approach The software consists of three modules. Firstly, the vision module has two tasks: to determine whether there is a human presence and to measure the distance between the robot and the human within the robot’s working space using convolutional neural networks (CNNs) and depth sensors. Secondly, the touch detection module perceives whether or not a human physically touches the robot within the same work environment using robot axis torques, wavelet packet decomposition algorithm and CNN. Lastly, the robot’s operating speed is adjusted according to hazard levels came from vision and touch module using the robot’s control module. Findings The developed software was tested with an industrial robot manipulator and successful results were obtained with minimal error. Practical implications The success of the developed algorithm was demonstrated in the current study and the algorithm can be used in other industrial robots for safety. Originality/value In this study, a new and practical safety algorithm is proposed and the health of people working with industrial robots is guaranteed.


2008 ◽  
Vol 5 (4) ◽  
pp. 213-223 ◽  
Author(s):  
Shuhei Ikemoto ◽  
Takashi Minato ◽  
Hiroshi Ishiguro

In this paper, we investigate physical human–robot interaction (PHRI) as an important extension of traditional HRI research. The aim of this research is to develop a motor learning system that uses physical help from a human helper. We first propose a new control system that takes advantage of inherent joint flexibility. This control system is applied on a new humanoid robot called CB2. In order to clarify the difference between successful and unsuccessful interaction, we conduct an experiment where a human subject has to help the CB2robot in its rising-up motion. We then develop a new measure that demonstrates the difference between smooth and non-smooth physical interactions. An analysis of the experiment’s data, based on the introduced measure, shows significant differences between experts and beginners in human–robot interaction.


2011 ◽  
Vol 23 (3) ◽  
pp. 451-457
Author(s):  
Eun-Sook Jee ◽  
◽  
Chong Hui Kim ◽  
Hisato Kobayashi ◽  
◽  
...  

Sound is an important medium for human-robot interaction. Single sound or music clip is not enough to express delicate emotions, especially it is almost impossible to represent emotional changings. This paper tries to express different emotional levels of sounds and their transitions. In this paper, happiness, sadness, anger, and surprise are considered as a basic set of robots’ emotion. By using previous proposed nominal sound clips of the four emotions, this paper proposes a method to reproduce the different emotional levels of sounds by modulating their musical parameters ‘tempo,’ ‘pitch,’ and ‘volume.’ Basic experiments whether human subject can discern three different emotional intensity levels of the four emotions are carried out. By comparing the recognition rate, the proposed modulation works fairly well and at least shows possibility of letting humans identify three intensity levels of emotions. Since the modulation can be done by dynamically changing the three musical parameters of sound clip, our method can be expanded to dynamical changing of emotional sounds.


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